L'émergence d'une économie de la défense fondée sur la connaissance : quelques leçons tirées des réformes au Royaume-uni
Bibliographic record
Abstract
Cette contribution analyse la restructu ration des liens entre l'État, l'industrie et la recherche dans l'organisation et l'exécution de projets de défense au Royaume-Uni, comme un processus de tâtonnement continu entre les forces de marché et les exigences de l'économie de la connaissance. L'analyse est fondée sur une rétrospective des décisions prises par le Ministry of Defense (MoD) depuis le milieu des années quatre-vingt : de l'application du principe de best value for money, jusqu'à la privatisation à travers QinetiQ, une grande partie des forces de recherche militaire. Cet examen montre que l'arbitrage permanent effectué par le MoD entre les considéra tions marchandes et cognitives dans la recherche de l'efficacité économique a abouti a la mise en place de modes de gouvernance hybrides (notamment sous forme de diverses plates-formes d'acteurs en réseau au sein desquels cohabitent et sont combinés des mécanismes à la fois marchands et partena-riaux.)
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.012 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".